Voting-based methods attempt to infer the pose of an object by accumulating evidence from local or global features of image patches.
One example is the Latent-Class Hough Forest [1]}, [2]} which adapts the template feature from [3]} for generating training data.
During inference stage, a random set of patches is sampled from the input image.
The patches are used in Hough voting to obtain pose hypotheses for verification.
